Experimental AI Research (Beta): This report was generated with AI assistance as part of our ongoing exploration of AI-powered research and analysis. The content has been reviewed and edited by humans, but may contain errors or inaccuracies.
Please verify critical data points independently. All claims cite public sources for transparency and reproducibility. This is not peer-reviewed academic research – treat findings as exploratory insights requiring further validation.
Cite This Report
Alice Labs Research (2026). GenAI Adoption Index – Sweden 2026. Alice Labs. https://alicelabs.ai/reports/genai-adoption-index-sweden-2026
Executive Summary
Sweden has emerged as a European leader in generative AI adoption, with enterprise usage more than tripling between 2023 and 2025. This GenAI Adoption Index provides a comprehensive, data-driven analysis of how Swedish businesses, public sector, and the general population are embracing generative AI technologies.
The adoption surge is unmistakable: 35% of Swedish enterprises now use AI (up from just 10.4% in 2023), placing Sweden third in the EU behind Denmark (42%) and Finland (38%). Large enterprises lead with 71.9% adoption, while SMEs are catching up – though a persistent digital divide remains.
The ICT sector dominates with 87.9% adoption, but traditional sectors like Transport & Storage lag significantly at just 12.2%. Marketing and administrative processes are the primary use cases, reflecting GenAI's strength in content generation and knowledge work automation.
- 35% of Swedish enterprises (≥10 employees) use AI in 2025, up from 10.4% in 2023 — a 236% increase
- 74.7% of non-adopting companies cite lack of AI expertise as the main barrier
- 25% of the Swedish population has used generative AI tools (50% among ages 16-24)
- 90% of Swedish municipalities have at least one AI initiative in operation
- 77% of Swedish companies provide AI-related training to employees
This report contains no interviews or anecdotes. All claims are reproducible from the cited public sources.
Key Findings
10 data-driven insights
01Enterprise AI adoption tripled in two years
35.0% of enterprises (≥10 employees) reported using AI in 2025, up from 10.4% in 2023
This 236% increase signals that AI has moved from pilot stage to operational reality for over one-third of Swedish businesses, largely driven by accessible GenAI tools like ChatGPT.
02Lack of skilled personnel is the #1 barrier to AI adoption
74.7% of non-AI-adopting firms cite 'lack of relevant in-house expertise' as the main barrier
Despite Sweden's highly educated workforce, demand for AI talent far exceeds supply. Three-quarters of companies wanting to adopt AI can't find the skills to do so.
03ICT sector leads with near-universal AI adoption
87.9% of Information & Communication companies use AI – nearly 9 in 10
AI (including GenAI) is no longer optional in tech – it's become part of the standard product offering and internal operations for the vast majority of ICT firms.
04Large enterprises pull away from SMEs in AI race
71.9% of large firms use AI vs. 30.8% of small firms – a 41 percentage point gap
The gap widened from 33 points in 2021 to 41 points in 2025. Without intervention, SMEs risk falling further behind in productivity and competitiveness.
05Half of young Swedes already use generative AI
50% of 16-24 year olds have used GenAI in the past 3 months, vs just 4% of those aged 65-74
GenAI is becoming second nature for the next generation of workers. The massive age gap also signals a potential digital divide requiring attention for older demographics.
0690% of Swedish municipalities are implementing AI
~90% of municipalities have at least one AI initiative, with 1000+ local AI projects nationwide
Sweden's public sector engagement with AI is exceptional internationally. Common applications include AI-assisted healthcare, citizen chatbots, and administrative automation.
07High-income workers use GenAI at twice the rate of low-income workers
72% of high-income vs 36% of low-income office workers use GenAI regularly at work
A socio-economic divide in GenAI adoption risks widening productivity gaps. Those already well-compensated gain further advantages through AI-enhanced work.
08Marketing and admin dominate AI use cases
41.7% of AI-using firms apply it to marketing/sales, 35.0% to business administration
GenAI's strength in text generation explains the concentration in marketing content and administrative tasks – the 'low-hanging fruit' of AI adoption.
09Majority of companies now use off-the-shelf AI solutions
62.1% of AI-adopting enterprises use commercial ready-made AI systems (up from 54% in 2023)
The shift to SaaS AI tools (ChatGPT, Copilot, etc.) has dramatically lowered barriers to adoption, enabling companies without AI expertise to still leverage the technology.
10Sweden ranks 3rd in EU but 25th globally for AI readiness
35% enterprise adoption (3rd in EU), but ranked 25th in Tortoise Global AI Index
High adoption doesn't equal leadership. Sweden lags behind major economies on talent, infrastructure, and research output factors that determine global AI competitiveness.
Introduction
Generative AI has fundamentally changed Sweden's digital landscape. Since ChatGPT's public release in November 2022, and subsequent waves of GenAI tools (GitHub Copilot, DALL-E, Midjourney, Claude), Swedish organizations have moved rapidly from curiosity to adoption.
Why This Report Matters
This GenAI Adoption Index aims to provide a comprehensive, transparent snapshot of where Sweden stands in early 2026. Unlike anecdotal reports or vendor surveys, we rely exclusively on official statistics (primarily Statistics Sweden and Eurostat) supplemented by reputable industry surveys.
Defining Generative AI
For this report, generative AI (GenAI) refers to AI systems capable of creating new content – text, images, audio, code – that is often indistinguishable from human-created content. Examples include large language models (GPT-4, Claude), image generators (DALL-E, Stable Diffusion), and code assistants (GitHub Copilot).
What Counts as "Adoption"
We define adoption as the implementation or use of AI technologies in regular workflows, products, or decision-making. It includes partial and experimental use in real settings – a company running a limited ChatGPT pilot for customer support counts as adoption.
Importantly, "adoption" does not necessarily mean full deployment at scale. Many adopters are still in early stages. High adoption rates should not be conflated with advanced maturity.
Data Visualizations
The following interactive visualizations present the key data points from the GenAI Adoption Index. Each chart is derived from official statistics and industry surveys, with sources noted below each visualization.
236%
Growth since 2023
#3
In EU adoption
74.7%
Skills gap barrier
2.1M
Swedes using GenAI
Enterprise AI Adoption in Sweden
% of enterprises (≥10 employees) using AI technology
Source: Statistics Sweden (SCB), 2021-2025
AI Adoption by Company Size
% of companies using AI by employee count (2025)
Source: Statistics Sweden (SCB), 2025
Key Insight: Enterprise AI adoption in Sweden has grown 236% since 2023, driven primarily by accessible GenAI tools. Large enterprises (250+ employees) lead at 71.9% adoption, while small firms (10-49) trail at 30.8% — a 41 percentage point gap.
AI Adoption by Industry Sector
% of companies using AI by sector (2025)
Source: Statistics Sweden (SCB), Alice Labs analysis, 2025
Barriers to AI Adoption
% of non-adopting companies citing each barrier
Source: Statistics Sweden (SCB), 2025
GenAI Usage by Age Group
% of population using GenAI in past 3 months (2024)
Source: Statistics Sweden (SCB), 2024
AI Use Cases in Swedish Enterprises
% of AI-adopting companies by purpose
- Marketing & Sales
- Administration
- Production
- R&D
- IT Security
- Logistics
Source: Statistics Sweden (SCB), 2025
Digital Divide Alert
Adoption gaps risk widening inequality
GenAI Usage by Income Level
% of office workers using GenAI regularly at work
High-income workers use GenAI at twice the rate, risking widening productivity gaps
Source: Solita (Kantar/Sifo), 2026
EU Enterprise AI Adoption Comparison
% of enterprises using AI (2025)
Source: Eurostat, Statistics Sweden, 2025
Interactive Data
All visualizations are interactive. Hover over chart elements for detailed data points. Raw data is available for download in the Scoreboard section below.
Sweden GenAI Scoreboard 2026
The GenAI Adoption Scoreboard compiles 20 key indicators from official and reputable sources. Each metric includes confidence levels: High for official statistics, Medium for industry surveys, Low for private analyses.
| Metric | Value | Year | Confidence |
|---|---|---|---|
| Enterprise AI adoption (2025) | 35.0% | 2025 | High |
| Enterprise AI adoption (2024) | 25.2% | 2024 | High |
| Enterprise AI adoption (2023) | 10.4% | 2023 | High |
| Large enterprise adoption | 71.9% | 2025 | High |
| Medium enterprise adoption | 49.6% | 2025 | High |
| Small enterprise adoption | 30.8% | 2025 | High |
| Micro enterprise adoption | 16.1% | 2025 | High |
| ICT sector adoption | 87.9% | 2025 | High |
| Transport sector adoption | 12.2% | 2025 | High |
| Barrier: Lack of expertise | 74.7% | 2025 | High |
| Barrier: Data protection | 49.1% | 2025 | High |
| Barrier: Data quality | 44.3% | 2025 | High |
| Population using GenAI | 25% | 2024 | High |
| GenAI usage (16-24 years) | 50% | 2024 | High |
| GenAI usage (65-74 years) | 4% | 2024 | High |
| Workers using ChatGPT | 30% | 2024 | Medium |
| Municipalities with AI | 90% | 2024 | Medium |
| Firms providing AI training | 77% | 2025 | Medium |
| EU GenAI adoption average | 37% | 2025 | High |
| Finland GenAI adoption | 66% | 2025 | High |
Interpretation
Sweden's 35% enterprise adoption rate (3rd in EU) reflects rapid GenAI-driven growth. The 74.7% skills barrier indicates that lack of expertise – not cost or regulation – is the primary obstacle. The size gap (72% large vs 31% small firms) and income gap (72% vs 36% among workers) suggest AI benefits are concentrating among those already advantaged. High public sector engagement (90% of municipalities) is a distinctive Swedish strength.
Adoption by Company Size
Adoption varies starkly by company size, revealing a persistent and growing digital divide between large enterprises and SMEs.
71.9%
Large (250+)
49.6%
Medium (50-249)
30.8%
Small (10-49)
16.1%
Micro (<10)
Growing Gap: The divide was ~33 percentage points in 2021 and grew to 41 points by 2025. Large firms jumped from 56.3% to 71.9% in a single year, while small firms increased more modestly from 22.0% to 30.8%.
Why This Matters
Bigger firms are pulling away in the AI-driven productivity race. They have better access to AI talent, can absorb implementation risks, and can afford enterprise licenses for GenAI services.
The Startup Exception
Among micro-enterprises, there's a bifurcation: innovative tech startups show extremely high adoption (~85% according to Notion Capital), while traditional small businesses lag significantly. The micro-firm average of 16.1% masks this divide.
Adoption by Industry
AI adoption varies widely across industries: certain sectors have raced ahead while others remain on the sidelines.
🚀 Leaders
📉 Laggards
Why Transport Lags
Many Swedish transport firms are small trucking companies that haven't fully digitized. Current AI/GenAI technologies may not suit physical logistics tasks as readily as they do knowledge work.
Public Sector Bright Spot
90% of Swedish municipalities have at least one AI initiative. This public sector engagement is exceptional internationally, driven by Vinnova and AI Sweden programs.
Use-Case Patterns
Clear patterns have emerged in how organizations deploy GenAI. Some use-cases dominate while others remain nascent.
Content generation, ad targeting, recommendations
Document drafting, email automation, HR screening
Quality control, predictive maintenance
Code assistance, research summarization
Threat detection, anomaly identification
Route optimization, inventory management
The GenAI Sweet Spot: Marketing and administration dominate because they involve text, communication, and data handling – exactly where GenAI excels.
Multi-Purpose Adoption Growing: 56% of large AI-using enterprises now deploy AI for two or more purposes. The trend is moving from single experiments to integrated multi-function use.
Workforce & Population Adoption
Beyond corporate statistics, individual adoption tells a story of rapid but uneven diffusion.
2.1M
Swedes have used GenAI in the past 3 months
25% of population age 16+
The Age Divide
16-24
50%
25-34
40%
35-44
29%
45-54
20%
65-74
4%
Gender Gap
29%
Men
20%
Women
9 percentage point gap
Income Divide
72%
High-income
36%
Low-income
2× difference risks widening inequality
Workplace Adoption: 52% of employed Swedes use at least one AI tool at work, and 30% have specifically used ChatGPT for work tasks.
Governance & Risk Practices
The surge in AI usage has often outpaced formal governance structures. Organizations are now actively working to catch up.
26%
Nordic CEOs directly involved in AI strategy
(vs 49% globally)
53%
Struggle to assign clear AI ownership
67%
Low concern about AI misinformation
Training as a Governance Lever
77% of Swedish companies now provide AI-related training to employees – the highest in the Nordics. This signals that many organizations are trying to build AI fluency and responsible use practices.
EU AI Act Preparation
The EU AI Act, enforceable by 2025/26, will require risk assessments, documentation, and transparency for high-risk AI systems. Swedish enterprises are beginning gap analyses.
Emerging Practices
- →From outright GenAI bans to nuanced policies: use for brainstorming/drafting, but review all outputs
- →Approved platforms (Azure OpenAI) while restricting public ChatGPT
- →Larger firms establishing AI ethics guidelines or internal AI councils
Barriers to Scaling
Despite rapid uptake, companies face significant barriers to scaling pilots into organization-wide capabilities.
74.7%
cite lack of expertise as the #1 barrier
Shortage of AI specialists, ML engineers, and AI-literate domain experts
Data protection concerns
GDPR compliance and privacy worries
Poor data quality/access
Data is messy, incomplete, or siloed
Costs too high
Scaling from pilot to production
Ethical considerations
Fairness, bias, transparency concerns
How Barriers Are Being Addressed
Skills
Government-funded AI education, company upskilling, international recruitment
Data
Investment in data warehousing, AI Sweden's Data Factory
Privacy
On-premises models, federated learning, regulatory sandboxes
Costs
Cloud scalability, open-source models, government grants
International Comparison
Sweden stands out as a European leader in AI adoption, though it faces stiff competition and is dwarfed by the AI superpowers.
EU Enterprise AI Adoption Rankings
Global Context: Sweden ranks #25 globally in the Tortoise Global AI Index. High adoption alone doesn't equal leadership – the index incorporates talent, infrastructure, research output, and investment.
🤝 Nordic Collaboration
The Nordic countries present a united "Nordic model" of adoption: high-trust societies implementing AI with consensus, strong welfare considerations, and focus on trustworthy AI. This model could become an international benchmark.
Where Sweden Lags
No Swedish company can invest like Google or Alibaba
US and India have far more AI specialists by volume
Supercomputing not matching US/China clusters
Outlook 2026–2028 (3 Scenarios)
We present three plausible scenarios for Sweden's GenAI trajectory over the next 2-3 years.
Scenario 1: "GenAI Everywhere"
OptimisticBy 2028, GenAI becomes as routine as email. Skills programs succeed, EU AI Act implemented without friction.
60-70%
Enterprise adoption
50-60%
Population usage
Scenario 2: "Integration, Not Revolution"
BaselineAdoption continues growing at moderate pace. Skills shortages persist but improve. Regulation adds overhead but doesn't stop adoption.
~50%
Enterprise adoption by 2028
Scenario 3: "Trust Erodes"
PessimisticHigh-profile AI failures trigger backlash. EU AI Act implemented restrictively. SMEs abandon AI efforts.
~40%
Adoption stalls
Key Determinants
Skills supply
Training pipeline delivery
Regulation clarity
EU AI Act interpretation
Trust
Public confidence
SME support
Resources for small firms
Recommendations (30/60/90 Days)
Practical, time-bound actions for Swedish organizations seeking to advance responsible GenAI adoption.
Immediate Actions
AI Task Force
Cross-functional team (IT, legal, HR, business) to own AI strategy
Usage Guidelines
Provide guardrails for employees already using ChatGPT
AI Audit
Inventory existing AI/GenAI use across the organization
Data Assessment
Identify key data sources and their quality/accessibility
Strategic Planning
Pilot Projects
Select 1-2 high-value, low-risk use cases
Training Programs
AI literacy for all; specialized training for key roles
Governance Framework
Policies on data handling, model oversight, human review
Stakeholder Engagement
Communicate with employees, unions, and customers
Institutionalization
Formalize Governance
Board-level oversight, clear accountability, ethics review
Scale Pilots
Move proven use cases into production with monitoring
Establish Metrics
KPIs for AI value (productivity, quality, cost savings)
Industry Initiatives
Join AI Sweden networks, working groups, sandboxes
Methodology
This report's analysis is built on a combination of quantitative data analysis, literature review, and contextual reasoning.
Data Collection
We gathered quantitative data from official statistics (Statistics Sweden's ICT usage surveys, Eurostat), reputable surveys (EY, Solita, CTA), and industry reports (Implement, Techstrong). All data points are cited with source references.
Comparative Analysis
To position Sweden internationally, we compared metrics across countries using harmonized Eurostat data where available. We normalized for structural differences when comparing absolute figures.
Trend Analysis
We examined 2021-2025 trends, noting inflection points (the big jump in 2024-2025 coinciding with GenAI introduction). This informed scenario projections.
Confidence Levels
Each metric is assigned a confidence level: High for official statistics with clear methodology, Medium for reputable surveys with smaller samples, Low for private analyses or estimates.
Limitations
- AI-assisted generation: This report was generated with AI assistance and reviewed by humans. While we strive for accuracy and cite all sources, AI-generated content may contain errors, hallucinations, or misinterpretations. Critical data points should be independently verified.
- Not peer-reviewed: This is exploratory research, not academic peer-reviewed work. Treat findings as insights requiring further validation rather than definitive conclusions.
- Data gaps on GenAI-specific adoption: Official statistics often measure "AI" broadly. We inferred GenAI uptake from overall AI data and specialized surveys.
- Recency of data: Most data is from late 2024 or 2025. In a fast-moving field, some findings may be outdated by publication.
- Survey response bias: Self-reported data from executives may carry optimism bias. We cross-checked against objective metrics where possible.
- Definition variations: Different sources define "AI adoption" differently, affecting comparability.
- SME underrepresentation: Large firms are overrepresented in some surveys. Small business AI adoption may be less accurately captured.
- Regional differences: National aggregates may mask urban-rural divides in adoption.
- Limited economic impact evidence: Hard evidence of AI's macro productivity impact in Sweden is still nascent.
Data Sources
12 primary sources
Version History
Initial publication. Comprehensive analysis across all sections.